Les outils Data Mining Open Source

Weka

Un livre est associé à ce développement :

Data Mining
Practical Machine Learning Tools and Techniques
Ian H. Witten , Eibe Frank
Morgan Kaufmann
550 Pages, 50,90€
Achat en ligne avec Eyrolles.com

4ème de couverture :
"As with any burgeoning technology that enjoys commercial attention, the use of data mining is surrounded by a great deal of hype. Exaggerated reports tell of secrets that can be uncovered by setting algorithms loose on oceans of data. But there is no magic in machine learning, no hidden power, no alchemy. Instead there is an identifiable body of practical techniques that can extract useful information from raw data. This book describes these techniques and shows how they work. The book is a major revision of the first edition that appeared in 1999. While the basic core remains the same, it has been updated to reflect the changes that have taken place over five years, and now has nearly double the references. The highlights for the new edition include thirty new technique sections; an enhanced Weka machine learning workbench, which now features an interactive interface; comprehensive information on neural networks; a new section on Bayesian networks; plus much more."

La suite du dossier Décisionnel Open Source

Au sommaire :

1 Le principe de l'Open Source

2 Les projets Open Source Intégration globale de la Business Intelligence
(Pentaho, Spago...)

3 Panorama des outils ETL Open Source
(Octopus, Clever.ETL, Kettle, Ketl)

4 Panorama des outils Reporting Open Source
(Jaspersoft, OpenReport, Birt, JfreeReport...)

5 Panorama des outils OLAP et Data Warehouse Open Source
(Palo, Mondrian, Jpivot, Pocolap, Golap...)

>>6 Les outils Data Mining Open Source
(Weka...)

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